Ranking statistically similar highway travel corridors using speed datasets within the USA

Abstract

Commercially available probe vehicle speed data are becoming a reliable means to evaluate roadway performance within the United States of America (USA). These temporally defined data are used to identify roadway congestion along fixed-location, variable-length highway segments called traffic message channels (TMC). Current performance measures that define congestion as an increase in travel time are inherently skewed towards longer, arbitrarily defined segments. To overcome this limitation, this paper defined congestion as the relative travel time increase, a performance measure that directly accounts for the variation in TMC lengths. Next, concurrent TMC with statistically similar levels of congestion were grouped into corridors. The resulting corridors provide a more accurate assessment of regional congestion, simplify data collection and analysis and allow agencies to compare congestion across different highway segments. The proposed methodology was applied to 83 TMCs along Interstate 80 East in New Jersey, USA. The 83 TMCs had in excess of 30 million speed records in 2013 for the AM peak period that were grouped into over 300 000 15 min intervals. An analysis of variance of time intervals indicated that the 83 TMCs could be grouped into 34 corridors. The congestion along each corridor was then characterised and visualised.